Bioinformatics scientist jobs in Finland
Bioinformatics scientists analyse biological processes using computer programmes. They maintain or construct databases containing biological information. Bioinformatics scientists gather and analyse biological data and may also assist scientists in various fields, including in biotechnology and pharmaceutics. They perform scientific research and statistical analyses, and report on their findings. Bioinformatics scientists may also collect DNA samples, discover data patterns and conduct genetic research.
Bioinformatics scientist - Which skills are essential?
Extract exportable data from multiple sources.
Maintain a freelance database that offers extra support to your teams and is able to calculate negotiating costs.
Utilise computer equipment or digital devices to facilitate quality control, data management, and communication. Follow instructions given by a computer programme, create computer files or documents.
Analyse data gathered from sources such as market data, scientific papers, customer requirements and questionnaires which are current and up-to-date in order to assess development and innovation in areas of expertise.
The techniques and principles of software development, such as analysis, algorithms, coding, testing and compiling of programming paradigms (e.g. object oriented programming, functional programming) and of programming languages.
Apply database design schemes and models, define data dependencies, use query languages and database management systems (DBMS) to develop and manage databases.
Collect data and statistics to test and evaluate in order to generate assertions and pattern predictions, with the aim of discovering useful information in a decision-making process.
Collect and analyse scientific data resulting from research. Interpret these data according to certain standards and viewpoints in order to comment on it.
Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.
Listen, reply, and establish a fluid communication relationship with scientists in order to extrapolate their findings and information into a varied array of applications including business and industry.
Use software tools for managing and organising data in a structured environment which consists of attributes, tables and relationships in order to query and modify the stored data.
Gain, correct or improve knowledge about phenomena by using scientific methods and techniques, based on empirical or measurable observations.
The programming paradigm that is based on combining markup (which adds context and structure to text) and other web programming code, such as AJAX, javascript and PHP, in order to carry out appropriate actions and visualise the content.
Apply scientific methods and techniques to investigate phenomena, by acquiring new knowledge or correcting and integrating previous knowledge.
The study of statistical theory, methods and practices such as collection, organisation, analysis, interpretation and presentation of data. It deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments in order to forecast and plan work-related activities.
Techniques applied in the different fields of natural science in order to obtain experimental data such as gravimetric analysis, gas chromatography, electronic or thermic methods.
Execute a systematic empirical investigation of observable phenomena via statistical, mathematical or computational techniques.
Engineering discipline that combines computer science with electrical engineering to develop computer hardware and software. Computer engineering occupies itself with electronics, software design, and the integration of hardware and software.
Tissues, cells, and functions of plant and animal organisms and their interdependencies and interactions with each other and the environment.
The offered computers, computer peripheral equipment and software products, their functionalities, properties and legal and regulatory requirements.
The tools for creating, updating and managing databases, such as Oracle, MySQL and Microsoft SQL Server.
Display results, statistics and conclusions to an audience in a transparent and straightforward way.
Assist engineers or scientists with conducting experiments, performing analysis, developing new products or processes, constructing theory, and quality control.
Collect biological specimens, record and summarise biological data for use in technical studies, developing environmental management plans and biological products.
Bioinformatics scientist - Which skills are useful but not essential?
Carry out tests in a laboratory to produce reliable and precise data to support scientific research and product testing.
Synthetise and write proposals aiming to solve research problems. Draft the proposal baseline and objectives, the estimated budget, risks and impact. Document the advances and new developments on the relevant subject and field of study.
Clean laboratory glassware and other equipment after use and inspect it for damage or corrosion in order to ensure its proper functioning.
The science that statistically analyses human characteristics such as retina, voice or DNA for identification purposes.
Mathematics is the study of topics such as quantity, structure, space, and change. It involves the identification of patterns and formulating new conjectures based on them. Mathematicians strive to prove the truth or falsity of these conjectures. There are many fields of mathematics, some of which are widely used for practical applications.
The study of heredity, genes and variations in living organisms. Genetic science seeks to understand the process of trait inheritance from parents to offspring and the structure and behaviour of genes in living beings.
Formulate scientific theories based on empirical observations, gathered data and theories of other scientists.
Collect data resulting from the application of scientific methods such as test methods, experimental design or measurements.
The interactions between the various systems of a cell, the interactions between the different types of genetic material and how these interactions are regulated.
Compose work-related reports that support effective relationship management and a high standard of documentation and record keeping. Write and present results and conclusions in a clear and intelligible way so they are comprehensible to a non-expert audience.
Develop and record the procedural method used for a specific scientific experiment in order to enable its replication.
Develop and manage methods and strategies used to maximise data quality and statistical efficiency in the collection of data, in order to ensure the gathered data are optimised for further processing.
Present the hypothesis, findings, and conclusions of your scientific research in your field of expertise in a professional publication.
Scientific activity consisting in selecting the relevant aspects of a situation and aiming to represent physical processes, empirical objects and phenomena to allow a better understanding, visualisation or quantification, and to enable simulation that shows how this particular subject would behave under given circumstances.
The process of revealing data issues using quality indicators, measures and metrics in order to plan data cleansing and data enrichment strategies according to data quality criteria.
Evaluate genetic data by applying statistical calculations and analysing the results.
Manipulation of the genetic material of an organism using methods that insert new DNA into or remove heritable material from the genome.
The theoretical methodology used in scientific research involving doing background research, constructing an hypothesis, testing it, analysing data and concluding the results.
Outline the research methodologies and schedule in order to ensure that the research can be thoroughly and efficiently executed and that the objectives can be met in a timely manner.